Abstract
Back-and-forth live migration, which means a running VM migrates between two physical machines back and forth, has several applications, such as “follow the moon” policy in data canter management. Traditional methods treat each migration as a single event, so the VM releases its system resources on the source site after migration. However, many resources can be kept to mit-igate the cost of the next migration back to the machine. This thesis proposes and implements performance optimization methods for back-and-forth live migration over WAN (BFMig). Different from previous work, our approach can keep the data center resiliency. We leverage the technique of snapshot and the bitmap model, which are available in most existing VM management systems. Using the snapshot, a VM can be immediately re-started from the saved state. The bitmaps model is used to avoid redundant data transmission to decrease the costs of migration. We implemented the bank-and-forth live migration optimization methods in QEMU-KVM 2.0. A performance model is also built to analyze the performance im-provement of our approaches. The experiments show that the proposed methods can significantly reduce the overhead of migrations. The total migration time can be saved up to 99% for some applications.